13 citations · 16 across the 8 of their papers we have counts for
9 papers
Towards Proactive Detection of User-Side Implicit Conflicts in Human-LLM Dialogue
Jinqiang Wang, Tao Zhu, Huansheng Ning
In Human-LLM dialogue, follow-up user utterances may implicitly conflict with earlier intents, leading the LLM to misinterpret user needs and generate inappropriate responses. A re…
PTMs-TSCIL Pre-Trained Models Based Class-Incremental Learning
Yuanlong Wu, Mingxing Nie, Tao Zhu +3
Class-incremental learning (CIL) for time series data faces critical challenges in balancing stability against catastrophic forgetting and plasticity for new knowledge acquisition,…
CTourLLM: Enhancing LLMs with Chinese Tourism Knowledge
Qikai Wei, Mingzhi Yang, Jinqiang Wang +3
Recently, large language models (LLMs) have demonstrated their effectiveness in various natural language processing (NLP) tasks. However, the lack of tourism knowledge limits the p…
A Survey on Large Language Models from General Purpose to Medical Applications: Datasets, Methodologies, and Evaluations
Jinqiang Wang, Huansheng Ning, Yi Peng +5
Large Language Models (LLMs) have demonstrated surprising performance across various natural language processing tasks. Recently, medical LLMs enhanced with domain-specific knowled…
ReLU-KAN: New Kolmogorov-Arnold Networks that Only Need Matrix Addition, Dot Multiplication, and ReLU
Qi Qiu, Tao Zhu, Helin Gong +2
Limited by the complexity of basis function (B-spline) calculations, Kolmogorov-Arnold Networks (KAN) suffer from restricted parallel computing capability on GPUs. This paper propo…
MCformer: Multivariate Time Series Forecasting with Mixed-Channels Transformer
Wenyong Han, Tao Zhu Member, Liming Chen +3
The massive generation of time-series data by largescale Internet of Things (IoT) devices necessitates the exploration of more effective models for multivariate time-series forecas…
HARMamba: Efficient and Lightweight Wearable Sensor Human Activity Recognition Based on Bidirectional Mamba
Shuangjian Li, Tao Zhu, Furong Duan +4
Wearable sensor-based human activity recognition (HAR) is a critical research domain in activity perception. However, achieving high efficiency and long sequence recognition remain…
P2LHAP:Wearable sensor-based human activity recognition, segmentation and forecast through Patch-to-Label Seq2Seq Transformer
Shuangjian Li, Tao Zhu, Mingxing Nie +3
Traditional deep learning methods struggle to simultaneously segment, recognize, and forecast human activities from sensor data. This limits their usefulness in many fields such as…
An Improved Masking Strategy for Self-supervised Masked Reconstruction in Human Activity Recognition
Jinqiang Wang, Tao Zhu, Huansheng Ning
Masked reconstruction serves as a fundamental pretext task for self-supervised learning, enabling the model to enhance its feature extraction capabilities by reconstructing the mas…